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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Systematic study of short- and long-range correlations in RE 3 TaO 7 weberite-type compounds by neutron total scattering and X-ray diffraction

The atomic structures of the lanthanide tantalates, Ln 3 TaO 7 , series (Ln = Pr, Tb, Dy, Ho, Tm, Yb) were systematically investigated using total scattering techniques. High-energy X-ray and neutron diffraction analysis revealed that the long-range structures can be grouped into three distinct families: (1) ordered Cmcm (Ln = Pr), (2) ordered Ccmm (Ln = Tb, Dy, Ho), and (3) disordered, defect-fluorite Fm$\bar{3}$m (Ln = Ho, Tm, Yb). These findings help to clarify the symmetry discrepancy for the already reported long-range structures in the literature. The short-range analysis of neutron total scattering data via pair distribution functions reveals a high degree of structural heterogeneity across length scales for all compounds, with distinct local atomic arrangements that are not fully captured by the average, long-range structure. The short-range structures at the level of coordination polyhedra are better captured by a set of alternative non-centrosymmetric structural models: (1) C2cm, (2) C222 1 , and (3) C2mm. This establishes a short-range multiferroic character for weberite-type tantalates because ferroelectric interactions compete with magnetic correlations. These ferroelectric interactions are particularly pronounced for the disordered compounds Tm 3 TaO 7 and Yb 3 TaO 7 . In conclusion, the structural differences among the three families are the result of changes in TaO 6 polyhedral tilt (transition between families 1 and 2) and dipolar interactions of off-centered Ta cations (transition between families 2 and 3).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Memory-Aware External Facelist Calculation: A Data-Parallel Atomic Hash Counting Approach

Unstructured volumetric meshes serve as fundamental data representations in various scientific simulations and analyses. They play a crucial role in representing complex computational domains and are essential for important numerical techniques, such as finite element analysis. Whenever such a mesh is read from a file, streamed in-situ, or generated by algorithms, scientific visualization libraries rely on calculating the external surface of a geometry, named “external facelist”, to produce a polygonal mesh for rendering. Consequently, external facelist calculation has become one of the most widely used algorithms in the scientific visualization domain, necessitating optimal performance. In this paper, we explore relevant work on external facelist calculation algorithms in two common visualization libraries, VTK and Viskores, assess their performance and memory constraints, and introduce a novel memory-aware external facelist calculation algorithm employing an atomic hash counting approach. This algorithm fully leverages Viskores' data-parallel primitive operations, facilitating its execution across diverse many-core architectures. Our algorithm features the lowest memory footprint on the GPU and the second-lowest on the CPU among all evaluated methods, and it also delivers the fastest performance on both CPU and GPU. It has been made available under an open-source license in the VTK and Viskores visualization systems.

Tsalikis, Spiros [Kitware] (ORCID:0000000151137195↗
DOE OSTI2025

Structure refinement and anisotropic atomic displacement parameters of 1M Illite: Rietveld and pair distribution function analysis using synchrotron X-ray radiation

Illite, a widespread clay mineral, plays a pivotal role in geological processes, notably as an indicator in diagenetic and hydrothermal alteration environments, and possesses significant industrial relevance in applications including ceramics, construction and catalysis. However, challenges including its nanoscale crystallinity, structural disorder and frequent interstratification with other clay minerals have hindered detailed structural characterization using conventional X-ray diffraction (XRD) techniques. This study employs integrated synchrotron XRD and pair distribution function (PDF) analysis to elucidate the crystal structure of the 1M illite polytype, yielding the first determination of its anisotropic atomic displacement parameters (U aniso ). TheseU aniso parameters provide critical insights into atomic dynamics and static disorder within the structure, enabling a more refined understanding of structure–property relationships. This integrated approach, combining synchrotron XRD, Rietveld refinement and PDF analysis, yields a comprehensive structural characterization, capturing both average crystallographic and local atomic arrangements. Considering illite's widespread geological occurrence and industrial importance, this high-precision structural dataset, especially the determinedU aniso values, provides a crucial benchmark for future modeling and simulation efforts targeting accurate prediction of its physicochemical behavior.

Chemistry↗
DOE OSTI2025

Variations in GARS powder microstructure as a function of powder chemistry and particle size

The properties of metal produced through powder metallurgy depends on the feedstock used. Powders produced via gas atomization reaction synthesis (GARS) are used to produce oxide dispersion strengthened alloys. The desired powder size range can vary for each consolidation technique. However, powder microstructure also can vary with powder particle size, which in turn can impact the microstructure and properties of the consolidated parts. In this study, GARS powders are characterized via inductively coupled plasma mass spectroscopy, inert gas fusion, and high-resolution x-ray diffraction to determine variations in elemental and phase compositions. Transmission electron microscopy was used to understand microstructure variations as a function of chemistry and size. Across the three batches tested intermetallic content was 0.73–1.35 wt% in the 0-20 μm powder batch and increased to 2.46–3.80 wt% in the coarse 45-106 μm batch. Across all batches, volume percent of surface oxidation decreased with powder diameter, with volume percents within the range of 0.75–1.2 % across 10 μm powder particles, and below 0.4 % across coarse powder particles approximately 100 μm in diameter. These observations were supported by inert gas fusion measurements. However, the oxide layer was thicker in coarse powder particles due to a slower cooling rate. Increasing oxygen content in atomization gas to 2000 ppm and adding yttrium increased both the surface oxidation content and yttrium intermetallic content. Lastly, intermetallic phases within the powder coarsened with powder size. Intermetallic morphology changed from fine spherical intermetallic and columnar dendritic growth to a cellular structure with finer spherical intermetallic, to coarse irregular intermetallic and intermetallic along grain boundaries as a result of slower cooling rate and solidification rate in coarse powder particles. Furthermore, the addition of zirconium does not appear to significantly change intermetallic morphology, but the composition changed from a Y-Fe rich intermetallic to a Y-Zr-Fe intermetallic.

42 ENGINEERING↗
DOE OSTI2025

AI-powered exploration of molecular vibrations, phonons, and spectroscopy

The vibrational dynamics of molecules and solids play a critical role in defining material properties, particularly their thermal behaviors. However, theoretical calculations of these dynamics are often computationally intensive, while experimental approaches can be technically complex and resource-demanding. Recent advancements in data-driven artificial intelligence (AI) methodologies have substantially enhanced the efficiency of these studies. This review explores the latest progress in AI-driven methods for investigating atomic vibrations, emphasizing their role in accelerating computations and enabling rapid predictions of lattice dynamics, phonon behaviors, molecular dynamics, and vibrational spectra. Key developments are discussed, including advancements in databases, structural representations, machine-learning interatomic potentials, graph neural networks, and other emerging approaches. Compared to traditional techniques, AI methods exhibit transformative potential, dramatically improving the efficiency and scope of research in materials science. The review concludes by highlighting the promising future of AI-driven innovations in the study of atomic vibrations.

Han, Bowen [Oak Ridge National Laboratory (ORNL), ↗
DOE OSTI2023

Photochemistry sample sticks for inelastic neutron scattering

Every material experiences atomic and molecular motions that are generally termed vibrations in gases and liquids or phonons in solid state materials. Optical spectroscopy techniques, such as Raman, infrared absorption spectroscopy, or inelastic neutron scattering (INS), can be used to measure the vibrational/phonon spectrum of ground state materials properties. A variety of optical pump probe spectroscopies enable the measurement of excited states or elucidate photochemical reaction pathways and kinetics. So far, it has not been possible to study photoactive materials or processes in situ using INS due to the mismatch between neutron and photon penetration depths, differences between the flux density of photons and neutrons, cryogenic temperatures for INS measurements, vacuum conditions, and a lack of optical access to the sample space. These experimental hurdles have resulted in very limited photochemistry studies using INS. Here we report on the design of two different photochemistry sample sticks that overcome these experimental hurdles to enable in situ photochemical studies using INS, specifically at the VISION instrument at Oak Ridge National Laboratory. We demonstrate the use of these new measurement capabilities through (1) the in situ photodimerization of anthracene and (2) the in situ photopolymerization of a 405 nm photoresin using 405 nm excitation as simple test cases. Furthermore, these new measurement apparatus broaden the science enabled by INS to include photoactive materials, optically excited states, and photoinitiated reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimizing the accuracy of viscoelastic characterization with AFM force–distance experiments in the time and frequency domains

Atomic Force Microscopy (AFM) force-distance (FD) experiments have emerged as an attractive alternative to traditional micro-rheology measurement techniques owing to their versatility of use in materials of a wide range of mechanical properties. Here, we show that the range of time dependent behaviour which can reliably be resolved from the typical method of FD inversion (fitting constitutive FD relations to FD data) is inherently restricted by the experimental parameters: sampling frequency, experiment length, and strain rate. Specifically, we demonstrate that violating these restrictions can result in errors in the values of the parameters of the complex modulus. In the case of complex materials, such as cells, whose behaviour is not specifically understood a priori, the physical sensibility of these parameters cannot be assessed and may lead to falsely attributing a physical phenomenon to an artifact of the violation of these restrictions. We use arguments from information theory to understand the nature of these inconsistencies as well as devise limits on the range of mechanical parameters which can be reliably obtained from FD experiments. The results further demonstrate that the nature of these restrictions depends on the domain (time or frequency) used in the inversion process, with the time domain being far more restrictive than the frequency domain. Lastly, we demonstrate how to use these restrictions to better design FD experiments to target specific timescales of a material's behaviour through our analysis of a polydimethylsiloxane (PDMS) polymer sample.

information theory↗
DOE OSTI2021

On the origin of internal obstacles to dislocation glide in single-phase NiFe random alloys

Over the past decade, a new class of unconventional alloys, where several constitutive elements are presented in close to equal concentrations, is considered as promising structural materials in many applications. Properties and behavior of many concentrated solid solution alloys (CSSAs) under different conditions, including mechanical loading, differs from that of conventional alloys and has been the subject of intensive studies by different techniques. A key feature of these materials is that there is no clear distinction between solute and solvent species of atoms, which is the conventional approach to considering dislocation motion in alloys. To understand this regime, we have recently reported on the glide of a screw dislocation glide in a simple equiatomic NiFe alloy and reported the two-mode character. At low applied stress, the dislocation motion is similar to a glide through a field of obstacles. In this work, we report the results of a detailed study on the nature of these internal obstacles. We demonstrate that these are not conventional localized “obstacles” but is the result of significantly different energies of instantaneous dislocation configurations over the alloy bulk. The strong pinning positions are associated with composition changes in the partial dislocation cores, while observing no significant composition changes along the stacking faults. Local energies can vary significantly, as demonstrated using simulations of short-periodicity dislocation lines. Therefore, the critical stress to move a dislocation under such conditions is not a constant Peierls stress but represents a wide spectrum of barriers between different non-straight valleys that the dislocation line accommodates in the bulk at particular stress/strain conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ultrasmooth Epitaxial Pt Thin Films Grown by Pulsed Laser Deposition

Platinum (Pt) thin films are useful in applications requiring high-conductivity electrodes with excellent thermal and chemical stability. Ultrasmooth and epitaxial Pt thin films with single-crystalline domains have the added benefit of providing ideal templates for the subsequent growth of heteroepitaxial structures. Here, we grow epitaxial Pt (111) electrodes (ca. 30 nm thick) on sapphire (α-Al 2 O 3 (0001)) substrates with pulsed laser deposition. This versatile technique allows control of the growth process and fabrication of films with carefully tailored parameters. X-ray scattering, atomic-force microscopy, and electron microscopy provide structural characterization of the films. Various gaseous atmospheres and temperatures were explored to achieve epitaxial growth of films with low roughness. A two-step (500 °C/300 °C) growth process was developed, yielding films with improved epitaxy without compromising roughness. The resulting films possess ultrasmooth interfaces (<3 Å) and high electrical conductivity (6.9 × 10 6 S/m). Finally, Pt films were used as current collectors and templates to grow lithium manganese oxide (LiMn 2 O 4 (111)) epitaxial thin films, a cathode material used in Li-ion batteries. In conclusion, using a solid-state ionogel electrolyte, the films were highly stable when electrochemically cycled in the 3.5-4.3 V vs Li/Li + range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimizing Materials to Boost the Valorization of CO 2 : Tuning Cobalt–Cobalt Interactions on In 2 O 3 -Based Photothermal Catalysts

The valorization of CO 2 is an important challenge within the current panorama, since this molecule is probably the main contributor to climate change. In this study, the synthesis of materials based on a nanostructured batonnet-type indium oxide is carried out. In them, different amounts of Co are introduced, varying between 2 and 8% mol. It is verified that the most active sample in the transformation of carbon dioxide to carbon monoxide contains 6 mol %. of Co. This sample’s activity under dual excitation exceeds the thermal counterpart by more than 30%. After carrying out a complete physical and chemical characterization with the help of X-ray absorption spectroscopy and other techniques, it is shown that catalysts with amounts of cobalt equal to or below 4 mol % contain isolated single-atom species, while those with higher amounts of metal display a Co–Co interaction which triggers the evolution of the samples under reaction conditions. The optimum control of this Co–Co interaction and the nature of the final cobalt-containing species determine dual photothermal catalytic properties. In conclusion, this work establishes a structure–activity relationship to interpret the catalytic behavior of highly dispersed subnanometric cobalt species, and thus an avenue to optimize the photothermal valorization of carbon dioxide.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bottom-up Assembly of Nanoporous Graphene with Emergent Electronic States

The incorporation of nanoscale pores into a sheet of graphene allows it to switch from an impermeable semimetal to a semiconducting nanosieve. Nanoporous graphenes are desirable for applications ranging from high-performance semiconductor device channels to atomically thin molecular sieve membranes, and their performance is highly dependent on the periodicity and reproducibility of pores at the atomic level. Achieving precise nanopore topologies in graphene using top-down lithographic approaches has proven to be challenging due to poor structural control at the atomic level. Alternatively, atomically precise nanometer-sized pores can be fabricated via lateral fusion of bottom-up synthesized graphene nanoribbons. This technique, however, typically requires an additional high temperature cross-coupling step following the nanoribbon formation that inherently yields poor lateral conjugation, resulting in 2D materials that are weakly connected both mechanically and electronically. Here, we demonstrate a novel bottom-up approach for forming fully conjugated nanoporous graphene through a single, mild annealing step following the initial polymer formation. We find emergent interface-localized electronic states within the bulk band gap of the graphene nanoribbon that hybridize to yield a dispersive two-dimensional low-energy band of states. We show that this low-energy band can be rationalized in terms of edge states of the constituent single-strand nanoribbons. The localization of these 2D states around pores makes this material particularly attractive for applications requiring electronically sensitive molecular sieves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Facile hermetic TEM grid preparation for molecular imaging of hydrated biological samples at room temperature

Abstract Although structures of vitrified supramolecular complexes have been determined at near-atomic resolution, elucidating in situ molecular structure in living cells remains a challenge. Here, we report a straightforward liquid cell technique, originally developed for real-time visualization of dynamics at a liquid-gas interface using transmission electron microscopy, to image wet biological samples. Due to the scattering effects from the liquid phase, the micrographs display an amplitude contrast comparable to that observed in negatively stained samples. We succeed in resolving subunits within the protein complex GroEL imaged in a buffer solution at room temperature. Additionally, we capture various stages of virus cell entry, a process for which only sparse structural data exists due to their transient nature. To scrutinize the morphological details further, we used individual particle electron tomography for 3D reconstruction of each virus. These findings showcase this approach potential as an efficient, cost-effective complement to other microscopy technique in addressing biological questions at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A multi-technique approach to understanding delithiation damage in LiCoO2 thin films

Abstract We report on the delithiation of LiCoO 2 thin films using oxalic acid (C 2 H 2 O 4 ) with the goal of understanding the structural degradation of an insertion oxide associated with Li chemical extraction. Using a multi-technique approach that includes synchrotron radiation X-ray diffraction, scanning electron microscopy, micro Raman spectroscopy, photoelectron spectroscopy and conductive atomic force microscopy we reveal the balance between selective Li extraction and structural damage. We identify three different delithiation regimes, related to surface processes, bulk delithiation and damage generation. We find that only a fraction of the grains is affected by the delithiation process, which may create local inhomogeneities. However, the bulk delithiation regime is effective to delithiate the LCO film. All experimental evidence collected indicates that the delithiation process in this regime mimics the behavior of LCO upon electrochemical delithiation. We discard the formation of Co oxalate during the chemical extraction process. In conclusion, the chemical route to Li extraction provides additional opportunities to investigate delithiation while avoiding the complications associated with electrolyte breakdown and simplifying in-situ measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Beyond electrical conductance: progress and prospects in single-molecule junctions

The idea of using individual molecules as conducting wires, regulators, and interconnects for charges in electronic circuitry has catalyzed the vibrant development of the field of single-molecule electronics. The ability to reliably and repeatedly construct single-molecule junctions (SMJs) has enabled the study of charge transport through a broad spectrum of individual molecules. Over the past decade, the capability of the SMJ platform has been greatly expanded thanks to the development of new experimental techniques and the integration of knowledge and methodologies from other disciplines. New opportunities beyond electrical conductance have emerged at the atomic and molecular scale. It has been demonstrated in many recent studies that the SMJ can now serve as a powerful and versatile tool to address critical physical and chemical questions that are otherwise inaccessible. Furthermore, this perspective focuses on the new capabilities and functionalities of the SMJ beyond conductance measurements and how they have enabled the investigation of crucial single-molecule processes and advanced our understanding beyond molecular electronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Pauli energy contribution to nucleus-nucleus interaction

The investigation delves into understanding how the Pauli exclusion principle influences the bare potential between atomic nuclei through the application of advanced theoretical methodologies. Specifically, the application of the novel Frozen-Hartree-Fock (DCFHF) technique is employed. The resulting potentials demonstrate a noticeable repulsion at short distances, attributed to the effects of the Pauli exclusion principle. To account for dynamic phenomena, such as nucleon transfer processes, the density-constrained time-dependent Hartree-Fock (DC-TDHF) method is utilized. This approach integrates isovector contributions into the potential, shedding light on their influence on fusion reactions. Notably, the inclusion of isovector effects leads to a reduction or enhancement in the inner part of the potential, suggesting a nuanced role of transfer in the fusion process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Electric-field-induced crossover of polarization reversal mechanisms in Al 1–x Sc x N ferroelectrics

Scandium-doped aluminum nitride, Al 1–x Sc x N, represents a new class of displacive ferroelectric materials with high polarization and sharp hysteresis along with high-temperature resilience, facile synthesizability and compatibility with standard CMOS fabrication techniques. The fundamental physics behind the transformation of unswitchable piezoelectric AlN into switchable Al–Sc–N ferroelectrics depends upon important atomic properties such as local structure, dopant distributions and the presence of competing mechanism of polarization switching in the presence of an applied electric-field that have not been understood. We computationally synthesize Al 1–x Sc x N to quantify the inhomogeneity of Sc distribution and phase segregation, and characterize its crystal and electronic structure as a function of Sc-doping. Nudged elastic band calculations of the potential energy surface and quantum molecular dynamics simulations of direct electric-field-driven ferroelectric switching reveal a crossover between two polarization reversal mechanisms—inhomogeneous nucleation-and-growth mechanism originating near Sc-rich regions in the limit of low applied fields and nucleation-limited-switching in the high-field regime. Finally, understanding polarization reversal pathways for these two mechanisms as well as the role of local Sc concentration on activation barriers provides design rules to identify other combinations of dopant elements, such as Zr, Mg etc. to synthesize superior AlN-based ferroelectric materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗